A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response

被引:332
作者
Bui, Van-Hai [1 ]
Hussain, Akhtar [1 ]
Kim, Hak-Man [1 ]
机构
[1] Incheon Natl Univ, Dept Elect Engn, Incheon 22012, South Korea
关键词
Adjustable power; demand response; energy management system; mixed integer linear programming; multiagent system; multi-microgrids; ENGINEERING APPLICATIONS; PART II; SYSTEM; OPERATION; SMART; ENVIRONMENT; MODEL;
D O I
10.1109/TSG.2016.2585671
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];
摘要
Conventionally, community energy management system (CEMS) is provided with the information of surplus and shortage amounts only at each time interval. This limited information may lead to an increase in the operational cost of the multimicrogrid (MMG) systems. This paper suggests informing the CEMS about the adjustable power also, in addition to the surplus and shortage information. This additional information will result in a variety of options for the CEMS to fulfill the load demands of its network. CEMS will choose among various available options, which include trading with the power grid, buying from a controllable distributed generation plant, buying from a community battery energy storage system (CBESS), or controlling the adjustable power: increasing or decreasing the generation of controllable units. CBESS can either be controlled by CEMS or can act as an autonomous entity. The effects of both the operational options have been analyzed and economically efficient mode is suggested for MMG systems. Demand response (DR) is also considered in the proposed model. The incorporation of DR will ensure the supply reliability of the MMG system in addition to the reduction in operational cost. In contrast to the conventional single or two-step multimicrogrid optimization algorithms, a multistep hierarchical optimization algorithm based on a multiagent system is proposed in this paper. Easy to implement and computationally inexpensive mixed integer linear programming models are developed for each step.
引用
收藏
页码:1323 / 1333
页数:11
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